<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Nie H</submitter><funding>Key Research and Development Program of the Department of Science and Technology of Ningxia Hui Autonomous Region</funding><pagination>e47249</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12851650</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>105(4)</volume><pubmed_abstract>This study aimed to identify autophagy-related genes with a causal role in ischemic stroke (IS) risk using a multi-omics Mendelian randomization (MR) approach. We integrated summary-level data for blood-derived DNA methylation (mQTLs), expression (eQTLs), and protein (pQTLs) quantitative trait loci for 594 autophagy-related genes with large-scale IS genome-wide association studies for discovery (GCST006908) and validation (FinnGen). Summary-data-based MR (SMR) with colocalization analysis was performed, supplemented by brain eQTL analysis, protein-protein interaction networking, and drug prediction. The analysis identified 113 mQTLs, 38 eQTLs, and 9 pQTLs associated with IS risk, with colocalization supporting shared causal variants for a subset. Validation in FinnGen confirmed 13 mQTLs an</pubmed_abstract><journal>Medicine</journal><pubmed_title>Autophagic molecular network in IS pathogenesis: A multi-omics Mendelian randomization study.</pubmed_title><pmcid>PMC12851650</pmcid><funding_grant_id>2021BEG03074</funding_grant_id><pubmed_authors>Hei Y</pubmed_authors><pubmed_authors>Zhang M</pubmed_authors><pubmed_authors>Zhang L</pubmed_authors><pubmed_authors>Ma T</pubmed_authors><pubmed_authors>Xu X</pubmed_authors><pubmed_authors>Nie H</pubmed_authors></additional><is_claimable>false</is_claimable><name>Autophagic molecular network in IS pathogenesis: A multi-omics Mendelian randomization study.</name><description>This study aimed to identify autophagy-related genes with a causal role in ischemic stroke (IS) risk using a multi-omics Mendelian randomization (MR) approach. We integrated summary-level data for blood-derived DNA methylation (mQTLs), expression (eQTLs), and protein (pQTLs) quantitative trait loci for 594 autophagy-related genes with large-scale IS genome-wide association studies for discovery (GCST006908) and validation (FinnGen). Summary-data-based MR (SMR) with colocalization analysis was performed, supplemented by brain eQTL analysis, protein-protein interaction networking, and drug prediction. The analysis identified 113 mQTLs, 38 eQTLs, and 9 pQTLs associated with IS risk, with colocalization supporting shared causal variants for a subset. Validation in FinnGen confirmed 13 mQTLs an</description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Jan</publication><modification>2026-06-12T10:17:06.074Z</modification><creation>2026-06-12T03:12:16.952Z</creation></dates><accession>S-EPMC12851650</accession><cross_references><pubmed>41578456</pubmed><doi>10.1097/MD.0000000000047249</doi></cross_references></HashMap>